Abstract: In the present invention, prior art techniques are extended to allow application of the backpropagation learning technique to artificial neural networks derived from fuzzy expert system rule-bases. A method in accordance with the invention, referred to herein as a Fuzzy Expert Network (FEN), is implemented in a programmed machine such as a computer to provide automated learning of both "fine" and "coarse" knowledge in a network of artificial neural objects (ANOs) implementing fuzzy modeling rules. Through application of the FEN method, an event-driven fuzzy expert network comprising acyclically connected ANOs derived from fuzzy modelling rules may be implemented. Neural objects implement one or more fuzzy combining and defuzzification rules and use backpropagation of error techniques to implement learning. As in prior art, the FEN allows each ANO to adjust its input weight parameters--"fine" knowledge learning.